A Rule-Based Approach to Sentiment Classification of Chinese Microblogging Texts

Abstract:

Chinese microblogging texts are always short and casual, which bring some troubles to the traditional sentiment classification methods based on learning. To overcome this problem, we use a rule-based approach to classify the sentiment of Chinese microblogging texts. According to the characteristics of Chinese microblogging texts, we construct a thesaurus of subjective words for it, summarize the basic semantic rules expressing emotion and propose a rule-based approach to sentiment classification of Chinese microblogging texts. Finally, we compare our approach with a SVM-based approach. Our rule-based approach achieves an accuracy of 0.865, which is better than that of SVM-based approach.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 1441-1445
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.1441
• Online since: September 2013
• Authors: Jia Jun Cheng, Xin Zhang, Peng Yi Fan, Pei Li, Hui Wang
• Keywords: Microblogging Texts in Chinese, Semantic Rule, Sentiment Classification

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